Update app.py

app.py

@@ -472,15 +472,31 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
                 
                 with gr.Column(scale=1):
                     gr.Markdown("### 🧠 Cognitive Instructions")
-                    cognitive_instructions = []
-                    for category, instructions in ADVANCED_CATEGORIES.items():
-                        with gr.Accordion(f"📌 {category}", open=False):
-                            checkbox_group = gr.CheckboxGroup(
-                                choices=instructions,
-                                label=category,
-                                value=[]
-                            )
-                            cognitive_instructions.append(checkbox_group)
+                    # Create individual components instead of a list
+                    with gr.Accordion("📌 Cognitive Techniques", open=False):
+                        cognitive_techniques = gr.CheckboxGroup(
+                            choices=ADVANCED_CATEGORIES["Cognitive Techniques"],
+                            label="Cognitive Techniques",
+                            value=[]
+                        )
+                    with gr.Accordion("📌 Output Structure", open=False):
+                        output_structure = gr.CheckboxGroup(
+                            choices=ADVANCED_CATEGORIES["Output Structure"],
+                            label="Output Structure",
+                            value=[]
+                        )
+                    with gr.Accordion("📌 Quality Assurance", open=False):
+                        quality_assurance = gr.CheckboxGroup(
+                            choices=ADVANCED_CATEGORIES["Quality Assurance"],
+                            label="Quality Assurance",
+                            value=[]
+                        )
+                    with gr.Accordion("📌 Audience Adaptation", open=False):
+                        audience_adaptation = gr.CheckboxGroup(
+                            choices=ADVANCED_CATEGORIES["Audience Adaptation"],
+                            label="Audience Adaptation",
+                            value=[]
+                        )
         
         # Style & Filtering Tab
         with gr.TabItem("🎨 Style & Filtering"):
@@ -573,6 +589,8 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
                 clear_chat_btn = gr.Button("🗑️ Clear", variant="secondary")
                 save_prompt_btn = gr.Button("💾 Save Prompt", variant="secondary")
             
+            save_status = gr.Textbox(label="💾 Save Status", visible=False, interactive=False)
+            
             chatbot = gr.Chatbot(
                 label="🤖 AI Assistant",
                 type="messages",
@@ -624,10 +642,14 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
                         lines=8,
                         interactive=False
                     )
+                    
+                    import_status = gr.Textbox(
+                        label="📥 Import Status",
+                        interactive=False
+                    )
 
     # State management
     chat_history = gr.State([])
-    current_template_vars = gr.State({})
 
     # Helper functions
     def update_template_info(category, template_name):
@@ -686,7 +708,7 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         
         return "", "", {}
 
-    def create_final_prompt(system, main_prompt, cognitive_selected, examples, tone, length, format_pref, role_persona, custom_system):
+    def create_final_prompt(system, main_prompt, cognitive_tech, output_struct, quality_assur, audience_adapt, examples, tone, length, format_pref, role_persona, custom_system):
         components = []
         
         # System prompt
@@ -699,7 +721,7 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         
         # Add cognitive instructions
         all_selected = []
-        for selected_list in cognitive_selected:
+        for selected_list in [cognitive_tech, output_struct, quality_assur, audience_adapt]:
             if selected_list:
                 all_selected.extend(selected_list)
         
@@ -733,13 +755,13 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         
         return "\n\n".join(components)
 
-    def process_chat_message(message, history, model, temp, system, cognitive_selected, tone, length, format_pref, role, custom_sys, banned_w, banned_p, *examples):
+    def process_chat_message(message, history, model, temp, system, cognitive_tech, output_struct, quality_assur, audience_adapt, tone, length, format_pref, role, custom_sys, banned_w, banned_p, *examples):
         if not message.strip():
             return history, history, "", {}, ""
         
         # Create final prompt
         final_prompt = create_final_prompt(
-            system, message, cognitive_selected, examples, 
+            system, message, cognitive_tech, output_struct, quality_assur, audience_adapt, examples, 
             tone, length, format_pref, role, custom_sys
         )
         
@@ -796,9 +818,12 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         
         return response_a, response_b
 
-    def save_current_prompt(prompt_name, final_prompt, model, stats):
-        if not prompt_name or not final_prompt:
-            return "❌ Please provide a name and ensure there's a prompt to save"
+    def save_current_prompt(final_prompt, model, stats):
+        # Simple prompt saving - in a real app you'd want a name input
+        prompt_name = f"Prompt_{len(state.saved_prompts)+1}_{datetime.now().strftime('%H%M')}"
+        
+        if not final_prompt:
+            return gr.update(value="❌ No prompt to save", visible=True)
         
         prompt_data = {
             "prompt": final_prompt,
@@ -808,14 +833,23 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         
         state.save_prompt(prompt_name, prompt_data)
         
-        # Update dropdown choices
-        choices = list(state.saved_prompts.keys())
-        return f"✅ Saved prompt '{prompt_name}'", gr.update(choices=choices)
+        return gr.update(value=f"✅ Saved as '{prompt_name}'", visible=True)
 
     def load_saved_prompt(prompt_name):
         if prompt_name in state.saved_prompts:
             return state.saved_prompts[prompt_name]
         return {}
+    
+    def delete_saved_prompt(prompt_name):
+        if prompt_name in state.saved_prompts:
+            del state.saved_prompts[prompt_name]
+            choices = list(state.saved_prompts.keys())
+            return gr.update(choices=choices, value=None), {}
+        return gr.update(), {}
+    
+    def update_saved_prompts_dropdown():
+        choices = list(state.saved_prompts.keys())
+        return gr.update(choices=choices)
 
     def refresh_analytics():
         analytics = calculate_analytics()
@@ -893,8 +927,8 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         process_chat_message,
         inputs=[
             chat_input, chat_history, selected_model, temperature,
-            custom_system, cognitive_instructions, tone_style, length_preference, 
-            format_preference, role_persona, custom_system, banned_words, banned_patterns,
+            custom_system, cognitive_techniques, output_structure, quality_assurance, audience_adaptation,
+            tone_style, length_preference, format_preference, role_persona, custom_system, banned_words, banned_patterns,
             example_1_input, example_1_output, example_2_input, example_2_output
         ],
         outputs=[chatbot, chat_history, final_prompt_preview, prompt_stats, optimization_display]
@@ -905,6 +939,12 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         outputs=[chatbot, chat_history]
     )
     
+    save_prompt_btn.click(
+        save_current_prompt,
+        inputs=[final_prompt_preview, selected_model, prompt_stats],
+        outputs=[save_status]
+    )
+    
     # A/B Testing
     test_btn.click(
         run_ab_test,
@@ -924,10 +964,30 @@ with gr.Blocks(css=custom_css, title="Ultimate LLM Prompt Builder", theme=gr.the
         outputs=[export_data]
     )
     
-    # Auto-refresh analytics on load
+    # Load and delete saved prompts
+    load_prompt_btn.click(
+        load_saved_prompt,
+        inputs=[saved_prompts_list],
+        outputs=[saved_prompt_display]
+    )
+    
+    delete_prompt_btn.click(
+        delete_saved_prompt,
+        inputs=[saved_prompts_list],
+        outputs=[saved_prompts_list, saved_prompt_display]
+    )
+    
+    # Import functionality
+    import_file.upload(
+        import_data,
+        inputs=[import_file],
+        outputs=[import_status]
+    )
+    
+    # Auto-refresh analytics on load and update saved prompts
     demo.load(
-        refresh_analytics,
-        outputs=[analytics_display, analytics_json]
+        lambda: (refresh_analytics()[0], refresh_analytics()[1], gr.update(choices=list(state.saved_prompts.keys()))),
+        outputs=[analytics_display, analytics_json, saved_prompts_list]
     )
 
 if __name__ == "__main__":